Fundamentals of Data Engineering
Plan and Build Robust Data Systems
Data engineering lifecycle foundations: generation, ingestion, orchestration, transformation, storage, and governance.
About the book
Essential primer for ML engineers building data pipelines. Reis and Housley walk through architecture patterns, cloud technology selection, and operational considerations for data systems. Understanding these fundamentals directly enables better ML systems.
Summary
Summary coming soon!